Tony Gonsolin

P Omaha Storm Chasers

Age 33 RHP 6'3" / 205 lbs AAA peak 0.3 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	AAAOklahoma City…	3	3	8	2.35	0.75	36.4%	6.1%	—	K 36.4% · BB 6.1% · FIP 0.80
2025	31	MIX2 levels	11	11	50	4.50	5.24	25.1%	11.2%	0.1	K 24.1% · BB 10.9% · FIP 5.24
2026	32	MIX2 levels	5	4	19	6.16	4.57	20.0%	8.8%	0.2	K 14.6% · BB 5.5% · FIP 4.43
2027PROJ	33	MLBKC	24	24	142	4.63	4.80	21.0%	9.3%	1.0
2028PROJ	34	MLBKC	14	14	86	4.92	5.11	20.1%	9.8%	0.3
2029PROJ	35	MLBKC	9	9	53	5.23	5.44	19.1%	10.3%	-0.0

Last 3 seasons WAR 0.3 · Next 3 projected WAR 1.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

K%61

FB Velo36

xwOBA vs17

CompsMike Burns (age 31) · Marco Quevedo (age 32) · Rolando Valdez (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 111

ERA4.63

FIP4.80

K%21.0%

BB%9.3%

K-BB%11.7%

Proj IP142

Value2027 · WAR

Runs saved vs league avg · 142 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3693.5

Whiff%

p8230.3%

p6124.2%

xwOBA vs

p170.351

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to the standard WAR scale.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2016	22	MIX MLE	2 levels	19	0	31	127	25	8	1	0%	1.6	13.9%	7.7%	6.1%	1.1%	3.77	3.51	—
2016	22	MIX RAW	2 levels	19	0	31	127	25	8	1	0%	1.6	19.7%	6.3%	13.4%	0.8%	3.77	2.68	—
2017	23	MIX MLE	2 levels	42	0	70	292	85	18	7	0%	1.7	21.7%	8.0%	13.7%	2.2%	3.86	3.50	—
2017	23	MIX RAW	2 levels	42	0	70	292	85	18	7	0%	1.7	29.1%	6.2%	22.9%	2.4%	3.86	2.74	—
2018	24	MIX MLE	2 levels	26	26	128	527	155	41	8	100%	4.9	23.0%	8.8%	14.2%	1.7%	2.60	3.21	—
2018	24	MIX RAW	2 levels	26	26	128	527	155	41	8	100%	4.9	29.4%	7.8%	21.6%	1.5%	2.60	2.45	—
2019	25	MIX MLE	2 levels	24	19	81	354	87	36	8	79%	3.4	22.9%	10.5%	12.4%	2.2%	3.65	3.72	+1.6
2019	25	MIX RAW	2 levels	24	19	81	354	87	36	8	79%	3.4	24.6%	10.2%	14.4%	2.3%	3.65	3.57	+1.8
2020	26	MLB MLE	Los Angeles Dodgers	9	8	47	176	46	7	2	89%	5.2	26.1%	4.0%	22.2%	1.1%	2.31	2.00	+2.1
2020	26	MLB RAW	Los Angeles Dodgers	9	8	47	176	46	7	2	89%	5.2	26.1%	4.0%	22.2%	1.1%	2.31	2.14	+2.0
2021	27	MIX MLE	3 levels	19	17	68	290	75	38	10	89%	3.6	27.2%	14.2%	13.0%	3.2%	3.29	4.37	+0.8
2021	27	MIX RAW	3 levels	19	17	68	290	75	38	10	89%	3.6	25.9%	13.1%	12.8%	3.4%	3.29	4.48	+0.7
2022	28	MIX MLE	2 levels	25	25	132	504	121	34	11	100%	5.3	23.9%	6.8%	17.1%	2.1%	2.11	3.11	+3.8
2022	28	MIX RAW	2 levels	25	25	132	504	121	34	11	100%	5.3	24.0%	6.7%	17.3%	2.2%	2.11	3.12	+3.7
2023	29	MIX MLE	2 levels	21	21	106	447	89	41	20	100%	5.0	18.9%	9.0%	9.9%	4.2%	5.01	4.94	+0.6
2023	29	MIX RAW	2 levels	21	21	106	447	89	41	20	100%	5.0	19.9%	9.2%	10.7%	4.5%	5.01	5.03	+0.4
2024	30	AAA MLE	Oklahoma City Baseball Club	3	3	8	33	12	2	0	100%	2.6	36.4%	6.1%	30.3%	0.0%	2.35	0.80	—
2024	30	AAA MLE	Oklahoma City Baseball Club	3	3	8	33	12	2	0	100%	2.6	36.4%	6.1%	30.3%	0.0%	2.35	0.80	—
2024	30	AAA RAW	Oklahoma City Baseball Club	3	3	8	33	12	2	0	100%	2.6	36.4%	6.1%	30.3%	0.0%	2.35	0.75	—
2025	31	MIX MLE	2 levels	11	11	50	215	54	24	11	100%	4.5	24.1%	10.9%	13.2%	5.1%	4.50	5.24	+0.1
2025	31	MIX MLE	2 levels	11	11	50	215	54	24	11	100%	4.5	24.1%	10.9%	13.2%	5.1%	4.50	5.24	+0.1
2025	31	MIX RAW	2 levels	11	11	50	215	54	24	11	100%	4.5	25.1%	11.2%	14.0%	5.1%	4.50	5.24	+0.1
2026	32	MIX MLE	2 levels	5	4	19	80	16	7	3	80%	3.8	14.6%	5.5%	9.0%	3.4%	6.16	4.43	+0.2
2026	32	MIX MLE	2 levels	5	4	19	80	16	7	3	80%	3.8	14.6%	5.5%	9.0%	3.4%	6.16	4.43	+0.2
2026	32	MIX RAW	2 levels	5	4	19	80	16	7	3	80%	3.8	20.0%	8.8%	11.3%	3.8%	6.16	4.57	+0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			87	78	414	1683	392	150	54	90%	4.8	23.3%	8.9%	14.4%	3.2%	3.43	3.99	+7.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	KC	24	24	142	600	126	56	21	100%	5.9	21.0%	9.3%	11.7%	3.5%	4.63	4.80	+1.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	KC	14	14	86	365	73	36	14	100%	6.2	20.1%	9.8%	10.3%	3.8%	4.92	5.11	+0.3
2029	35	MLB MLE	KC	9	9	53	223	43	23	9	100%	5.9	19.1%	10.3%	8.8%	4.1%	5.23	5.44	-0.0
2028	34	MLB CTX	KC	14	14	86	363	73	35	14	100%	6.1	20.1%	9.8%	10.3%	3.8%	4.92	5.11	+0.3
2029	35	MLB CTX	KC	9	9	53	224	43	23	9	100%	5.9	19.1%	10.3%	8.8%	4.1%	5.23	5.44	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		110	101	554	2271	508	209	77	92%	5.0	22.4%	9.2%	13.2%	3.4%	3.84	4.24	+7.6
/ 200 IP	—	RAW		40	37	200	820	184	76	28	92%	5.0	22.4%	9.2%	13.2%	3.4%	3.84	4.24	+2.7
Career	—	MLE		204	134	740	3045	688	269	79	66%	3.6	22.6%	8.8%	13.8%	2.6%	3.40	3.74	+7.2
/ 200 IP	—	MLE		55	36	200	823	186	73	21	66%	3.6	22.6%	8.8%	13.8%	2.6%	3.40	3.74	+2.6

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AAAOmaha Storm Chasers · 16 IPFIP 4.14 → 4.43 (+0.29)K% 16.9% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.92%	—	×0.860	14.55%
BB% (unintentional) /BF	6.15%	—	×0.900	5.54%
HR / BF /BF	3.08%	÷1.000	×1.100	3.38%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 4.14 → 4.43, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 AAAOklahoma City Comets · 14 IPFIP 3.97 → 4.45 (+0.48)K% 27.6% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.59%	—	×0.860	23.72%
BB% (unintentional) /BF	10.34%	—	×0.900	9.31%
HR / BF /BF	3.45%	÷0.956	×1.100	3.97%

Result: FIP 3.97 → 4.45, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 AAAOklahoma City Baseball Club · 8 IPFIP 0.80 → 1.15 (+0.35)K% 36.4% → 31.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.36%	—	×0.860	31.27%
BB% (unintentional) /BF	6.06%	—	×0.900	5.45%
HR / BF /BF	0.00%	÷0.896	×1.100	0.00%

Result: FIP 0.80 → 1.15, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 AAAOklahoma City Dodgers · 10 IPFIP 4.89 → 5.40 (+0.50)K% 22.5% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.880	19.80%
BB% (unintentional) /BF	7.50%	—	×1.050	7.88%
HR / BF /BF	5.00%	÷1.016	×1.100	5.41%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 103).

Result: FIP 4.89 → 5.40, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2019 AAAOklahoma City Dodgers · 41 IPFIP 3.43 → 3.80 (+0.36)K% 26.2% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.18%	—	×0.880	23.04%
BB% (unintentional) /BF	10.99%	—	×1.050	11.54%
HR / BF /BF	2.09%	÷1.073	×1.100	2.15%

Result: FIP 3.43 → 3.80, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 A+Rancho Cucamonga Quakes · 84 IPFIP 2.26 → 3.14 (+0.88)K% 30.5% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.55%	—	×0.770	23.52%
BB% (unintentional) /BF	7.49%	—	×1.150	8.62%
HR / BF /BF	1.44%	÷1.058	×1.250	1.70%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 112).

Result: FIP 2.26 → 3.14, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 AATulsa Drillers · 44 IPFIP 2.77 → 3.36 (+0.58)K% 27.2% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.22%	—	×0.810	22.05%
BB% (unintentional) /BF	8.33%	—	×1.100	9.17%
HR / BF /BF	1.67%	÷1.147	×1.200	1.74%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 129).

Result: FIP 2.77 → 3.36, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2017 A+Rancho Cucamonga Quakes · 62 IPFIP 2.66 → 3.50 (+0.84)K% 28.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.19%	—	×0.770	21.70%
BB% (unintentional) /BF	6.95%	—	×1.150	7.99%
HR / BF /BF	1.93%	÷1.085	×1.250	2.22%

Result: FIP 2.66 → 3.50, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Tony Gonsolin (OGILVIE)	—	—	—	—	—	3.5%	—	5.24	19.7%	9.8%	139	+0.44	—	—	—
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	64
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	63
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	58
Deck McGuire R 2022 · 5.12 FIP	33	SP-	5.12	15.7%	13.1%	3.1%	.279	—	—	—	—	—	3.41	622	58
Yohan Pino R 2017 · 5.33 FIP	33	SP-	5.33	15.2%	3.6%	5.6%	.296	—	—	—	—	—	3.84	193	56
Elih Villanueva R 2017 · 5.48 FIP	31	SP	5.48	14.1%	6.0%	5.1%	.365	—	—	—	—	—	3.83	225	56
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	55
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	55
Thad Weber R 2017 · 5.25 FIP	32	SP-	5.25	13.2%	4.4%	4.9%	.398	—	—	—	—	—	4.40	378	55
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	52
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	52
Kodai Senga R 2024 · 4.69 FIP	31	SP	4.69	14.9%	13.8%	2.0%	.324	4.51	24.0%	11.5%	175	-0.18	3.40	352	49
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	49
Mickey Jannis R 2021 · 5.68 FIP	33	SP-	5.68	12.1%	11.8%	3.8%	.303	—	—	—	—	—	2.82	659	49
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	49
Diego Moreno R 2019 · 4.08 FIP	32	SP	4.08	12.4%	6.9%	2.1%	.376	4.75	18.6%	9.2%	30	+0.67	2.29	187	49
Casey Lawrence R 2021 · 4.08 FIP	33	SP-	4.08	20.0%	5.2%	3.7%	.284	4.99	15.9%	10.6%	440	+0.91	3.57	1,374	48
Alfredo Figaro R 2016 · 3.75 FIP	32	SP-	3.75	10.2%	5.0%	1.6%	.270	—	—	—	—	—	3.75	143	48
Rodolfo Aguirre R 2017 · 5.96 FIP	32	SW	5.96	10.0%	13.0%	3.8%	.316	4.50	21.3%	16.2%	15	-1.46	3.39	212	48
Salvador Valdez R 2016 · 3.60 FIP	33	SP	3.60	12.8%	7.5%	1.1%	.310	3.99	11.5%	4.9%	138	+0.39	3.60	326	48

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	3.5	77	22.1%	9.3%	1.32	4.00
Chris Young ('17)	6.5	100	19.4%	9.2%	1.29	3.95
John Henry Johnson ('78-'87, 6 WAR*)	3.0	75	24.6%*	9.6%*	1.15*	4.15*
Frankie Montas ('25)	3.9	98	23.6%	8.2%	1.20	4.20
John Patterson ('07)	2.3	76	21.2%	9.1%	1.19	4.32
Bob Johnson ('69-'77, 6 WAR*)	3.5	115	23.4%*	8.9%*	1.49*	4.12*
Joe Hesketh ('84-'94, 10 WAR*)	4.8	87	23.2%*	8.8%*	1.07*	3.95*